The demand for a technique that is flexible and adaptive to changes of the environment while satisfying real-life constraints is rising, and DRL algorithms are among the most potential methods to deal with these problems in wireless networks [1]}, [2]}, [3]}, [4]}. Recently, DRL algorithms are also used for the RIS-assisted wireless networks and have shown promising results [5]}, [6]}, [7]}, [8]}, [9]}. The power allocation and the phase shift optimization were optimized for maximizing the sum rate in [5]}. In [6]}, a RIS-assisted UAV was deployed for serving ground users. The trajectory and phase shift optimization relying on DRL for maximizing the sum rate and fairness of all users was proposed. In [7]}, the authors used a RIS to assist the secure communications against eavesdroppers. The DRL algorithms were used to optimize the BS beamforming and the RIS's reflecting beamforming were shown to improve the secrecy rate and the quality-of-service satisfaction probability. In [8]}, deep deterministic policy gradient was proposed to obtain the optimal phase shift matrix at the RIS to maximize the received signal-to-noise ratio (SNR) in a MISO system. In [9]}, the joint optimization of the power and the RIS's phase shift in a multi-UAV-assisted network is considered.
